Danlu Guo

1.5k total citations
48 papers, 959 citations indexed

About

Danlu Guo is a scholar working on Water Science and Technology, Global and Planetary Change and Environmental Chemistry. According to data from OpenAlex, Danlu Guo has authored 48 papers receiving a total of 959 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Water Science and Technology, 18 papers in Global and Planetary Change and 15 papers in Environmental Chemistry. Recurrent topics in Danlu Guo's work include Hydrology and Watershed Management Studies (30 papers), Soil and Water Nutrient Dynamics (15 papers) and Water Quality and Pollution Assessment (13 papers). Danlu Guo is often cited by papers focused on Hydrology and Watershed Management Studies (30 papers), Soil and Water Nutrient Dynamics (15 papers) and Water Quality and Pollution Assessment (13 papers). Danlu Guo collaborates with scholars based in Australia, China and United States. Danlu Guo's co-authors include Holger R. Maier, Seth Westra, Andrew W. Western, Dongryeol Ryu, Shuci Liu, Anna Lintern, J. Angus Webb, Feifei Zheng, Conrad Wasko and Ulrike Bende‐Michl and has published in prestigious journals such as The Science of The Total Environment, Water Resources Research and Environmental Pollution.

In The Last Decade

Danlu Guo

45 papers receiving 947 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Danlu Guo Australia 18 617 458 254 125 115 48 959
Vishal K. Mehta United States 15 571 0.9× 299 0.7× 169 0.7× 222 1.8× 140 1.2× 43 866
A Yinglan China 18 514 0.8× 402 0.9× 307 1.2× 41 0.3× 128 1.1× 59 1.0k
S. Rehana India 18 544 0.9× 455 1.0× 275 1.1× 151 1.2× 33 0.3× 45 936
Vassilis Z. Antonopoulos Greece 16 352 0.6× 307 0.7× 324 1.3× 48 0.4× 109 0.9× 27 931
Shiying Tian United States 14 448 0.7× 239 0.5× 122 0.5× 121 1.0× 159 1.4× 37 786
H. G. Frede Germany 17 675 1.1× 451 1.0× 316 1.2× 68 0.5× 242 2.1× 27 1.2k
Kunxia Yu China 16 528 0.9× 460 1.0× 178 0.7× 52 0.4× 68 0.6× 59 1.0k
Jong Ahn Chun South Korea 21 589 1.0× 565 1.2× 494 1.9× 75 0.6× 181 1.6× 64 1.4k
Bano Mehdi Austria 16 408 0.7× 346 0.8× 173 0.7× 63 0.5× 197 1.7× 37 1.1k

Countries citing papers authored by Danlu Guo

Since Specialization
Citations

This map shows the geographic impact of Danlu Guo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Danlu Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danlu Guo more than expected).

Fields of papers citing papers by Danlu Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Danlu Guo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Danlu Guo. The network helps show where Danlu Guo may publish in the future.

Co-authorship network of co-authors of Danlu Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Danlu Guo. A scholar is included among the top collaborators of Danlu Guo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Danlu Guo. Danlu Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Guo, Danlu, Anna Lintern, Alexander H. Elliott, et al.. (2025). A commentary on strategic community-led directions for water quality modelling in Australia and New Zealand. Journal of Hydrology. 656. 132978–132978.
2.
Guo, Danlu, Qian Zhang, Camille Minaudo, et al.. (2025). Australian water quality trends over two decades show deterioration in the Great Barrier Reef region and recovery in the Murray-Darling Basin. Communications Earth & Environment. 6(1). 4 indexed citations
3.
4.
Fowler, Keirnan, Thomas A. McMahon, Seth Westra, et al.. (2024). Climate stress testing for water systems: Review and guide for applications. Wiley Interdisciplinary Reviews Water. 11(6). 7 indexed citations
5.
Guo, Danlu, et al.. (2023). How does wildfire and climate variability affect streamflow in forested catchments? A regional study in eastern Australia. Journal of Hydrology. 625. 129979–129979. 9 indexed citations
6.
Lintern, Anna, et al.. (2023). Shifts in stream salt loads during and after prolonged droughts. Hydrological Processes. 37(6). 1 indexed citations
7.
Guo, Danlu, Quan J. Wang, Dongryeol Ryu, et al.. (2022). An analysis framework to evaluate irrigation decisions using short-term ensemble weather forecasts. Irrigation Science. 41(1). 155–171. 17 indexed citations
8.
9.
Guo, Danlu, Camille Minaudo, Anna Lintern, et al.. (2022). Synthesizing the impacts of baseflow contribution on concentration–discharge ( C – Q ) relationships across Australia using a Bayesian hierarchical model. Hydrology and earth system sciences. 26(1). 1–16. 12 indexed citations
10.
Bennett, Bree, et al.. (2021). A modelling framework and R-package for evaluating system performance under hydroclimate variability and change. Environmental Modelling & Software. 139. 104999–104999. 13 indexed citations
11.
Liu, Shuci, Dongryeol Ryu, J. Angus Webb, et al.. (2021). A multi-model approach to assessing the impacts of catchment characteristics on spatial water quality in the Great Barrier Reef catchments. Environmental Pollution. 288. 117337–117337. 20 indexed citations
12.
Liu, Shuci, Dongryeol Ryu, J. Angus Webb, et al.. (2021). A Bayesian approach to understanding the key factors influencing temporal variability in stream water quality – a case study in the Great Barrier Reef catchments. Hydrology and earth system sciences. 25(5). 2663–2683. 18 indexed citations
13.
14.
Guo, Danlu, Anna Lintern, J. Angus Webb, et al.. (2020). A data-based predictive model for spatiotemporal variability in stream water quality. Hydrology and earth system sciences. 24(2). 827–847. 37 indexed citations
15.
Liu, Shuci, Danlu Guo, J. Angus Webb, Paul J. Wilson, & Andrew W. Western. (2020). A simulation-based approach to assess the power of trend detection in high- and low-frequency water quality records. Environmental Monitoring and Assessment. 192(10). 628–628. 6 indexed citations
16.
Guo, Danlu, Anna Lintern, J. Angus Webb, et al.. (2019). A predictive model for spatio-temporal variability in stream water quality. 2 indexed citations
17.
Liu, Shuci, Dongryeol Ryu, J. Angus Webb, et al.. (2018). Characterisation of spatial variability in water quality in the Great Barrier Reef catchments using multivariate statistical analysis. Marine Pollution Bulletin. 137. 137–151. 34 indexed citations
18.
Guo, Danlu, Anna Lintern, J. Angus Webb, et al.. (2018). Key Factors Affecting Temporal Variability in Stream Water Quality. Water Resources Research. 55(1). 112–129. 84 indexed citations
19.
Guo, Danlu, Seth Westra, & Holger R. Maier. (2017). Sensitivity of potential evapotranspiration to changes in climate variables for different Australian climatic zones. Hydrology and earth system sciences. 21(4). 2107–2126. 95 indexed citations
20.
Feng, Zhihua, et al.. (2015). Physiological responses and quality attributes of Jiashi muskmelon (Cucurbitaceae, Cucumis melo L.) following postharvest hydrogen peroxide treatment during storage. European Journal of Horticultural Science. 80(6). 288–295. 13 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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